Tag Archives: data validation

Will your application consolidation or migration go live on time and on budget? According to Gartner, “through 2019, more than 50% of data migration projects will exceed budget and/or result in some form of business disruption due to flawed execution.”1That is a scary number by any measure. A colleague of mine put it well: ‘I wouldn’t get on a plane that had 50% chance of failure’. So should you be losing sleep over your migration or consolidation project? Well that depends. Are you the former CIO of Levi Strauss? Who, according to Harvard Business Review, was forced to resign due to a botched SAP migration project and a $192.5million earnings write-off?2 If so, perhaps you would feel a bit apprehensive. Otherwise, I say you can be cautiously optimistic, if you go into it with a healthy dose of reality. Please ensure you have a good understanding of the potential pitfalls and how to address them. You need an appreciation for the myths and realities of application consolidation and migration.

First off, let me get one thing off my chest. If you don’t pay close attention to your data, throughout the application consolidation or migration process, you are almost guaranteed delays and budget overruns. Data consolidation and migration is at least 30%-40% of the application go-live effort. We have learned this by helping customers deliver over 1500 projects of this type. What’s worse, if you are not super meticulous about your data, you can be assured to encounter unhappy business stakeholders at the end of this treacherous journey. The users of your new application expect all their business-critical data to be there at the end of the road. All the bells and whistles in your new application will matter naught if the data falls apart. Imagine if you will, students’ transcripts gone missing, or your frequent-flyer balance a 100,000 miles short! Need I say more? Now, you may already be guessing where I am going with this. That’s right, we are talking about the myths and realities related to your data! Let’s explore a few of these.

Myth #1: All my data is there.

Reality #1: It may be there… But can you get it? if you want to find, access and move out all the data from your legacy systems, you must have a good set of connectivity tools to easily and automatically find, access and extract the data from your source systems. You don’t want to hand-code this for each source. Ouch!

Myth #2: I can just move my data from point A to point B.

Reality #2: You can try that approach if you want. However you might not be happy with the results. Reality is that there can be significant gaps and format mismatches between the data in your legacy system and the data required by your new application. Additionally you will likely need to assemble data from disparate systems. You need sophisticated tools to profile, assemble and transform your legacy data so that it is purpose-fit for your new application.

Myth #3: All my data is clean.

Reality #3: It’s not. And here is a tip: better profile, scrub and cleanse your data before you migrate it. You don’t want to put a shiny new application on top of questionable data . In other words let’s get a fresh start on the data in your new application!

Myth #4: All my data will move over as expected

Reality #4: It will not. Any time you move and transform large sets of data, there is room for logical or operational errors and surprises. The best way to avoid this is to automatically validate that your data has moved over as intended.

Myth #5: It’s a one-time effort.

Reality #5: ‘Load and explode’ is formula for disaster. Our proven methodology recommends you first prototype your migration path and identify a small subset of the data to move over. Then test it, tweak your model, try it again and gradually expand. More importantly, your application architecture should not be a one-time effort. It is work in progress and really an ongoing journey. Regardless of where you are on this journey, we recommend paying close attention to managing your application’s data foundation.

As you can see, there is a multitude of data issues that can plague an application consolidation or migration project and lead to its doom. These potential challenges are not always recognized and understood early on. This perception gap is a root-cause of project failure. This is why we are excited to host Philip Russom, of TDWI, in our upcoming webinar to discuss data management best practices and methodologies for application consolidation and migration. If you are undertaking any IT modernization or rationalization project, such as consolidating applications or migrating legacy applications to the cloud or to ‘on-prem’ application, such as SAP, this webinar is a must-see.

So what’s your reality going to be like? Will your project run like a dream or will it escalate into a scary nightmare? Here’s hoping for the former. And also hoping you can join us for this upcoming webinar to learn more:

How would you like to wake up to an extra billion dollars, or maybe nine, in the bank? This has happened to a teacher in India. He discovered to his astonishment a balance of $9.8 billion in his bank account!

How would you like to be the bank who gave the client an extra nine Billion dollars? Oh, to be a fly on the wall when the IT department got that call. How do you even begin to explain? Imagine the scrambling to track down the source of the data error.

This was a glaringly obvious error, which is easily caught. But there is potential for many smaller data errors. These errors may go undetected and add up hurting your bottom line. How could this type of data glitch happen? More importantly, how can you protect your organization from these types of errors in your data?

A primary source of data mistakes is insufficient testing during Data Integration. Any change or movement of data harbors risk to its integrity. Unfortunately there are often insufficient IT resources to adequately validate the data. Some organizations validate the data manually. This is a lengthy, unreliable process, fraught with data errors. Furthermore manual testing does not scale well to large data volumes or complex data changes. So the validation is often incomplete. Finally some organizations simply lack the resources to conduct any level of data validation altogether.

Many of our customers have been able to successfully address this issue via automated data validation testing. (Also known as DVO). In a recent TechValidate survey, Informatica customers have told us that they:

Reduce costs associated with data testing.

Reduce time associated with data testing.

Increase IT productivity.

Increase the business trust in the data.

Customers tell us some of the biggest potential costs relate to damage control which occurs when something goes wrong with their data. The tale above, of our fortunate man and not so fortunate bank, can be one example. Bad data can hurt a company’s reputation and lead to untold losses in market-share and customer goodwill. In today’s highly regulated industries, such as healthcare and financial services, consequences of incorrect data can be severe. This can include heavy fines or worse.

Using automated data validation testing allows customers to save on ongoing testing costs and deliver reliable data. Just as important, it prevents pricey data errors, which require costly and time-consuming damage control. It is no wonder many of our customers tell us they are able to recoup their investment in less than 12 months!

TechValidate survey shows us that customers are using data validation testing in a number of common use cases including:

Regression (Unit) testing

Application migration or consolidation

Software upgrades (Applications, databases, PowerCenter)

Production reconciliation

One of the most beneficial use cases for data validation testing has been for application migration and consolidation. Many SAP migration projects undertaken by our customers have greatly benefited from automated data validation testing. Application migration or consolidation projects are typically large and risky. A Bloor Research study has shown 38% of data migration projects fail, incurring overages or are aborted altogether. According to a Harvard Business Review article, 1 in 6 large IT projects run 200% over budget. Poor data management is one of the leading pitfalls in these types of projects. However, according to Bloor Research, Informatica’ s data validation testing is a capability they have not seen elsewhere in the industry.

A particularly interesting example of above use case is in the case of M&A situation. The merged company is required to deliver ‘day-1 reporting’. However FTC regulations forbid the separate entities from seeing each other’s data prior to the merger. What a predicament! The automated nature of data validation testing, (Automatically deploying preconfigured rules on large data-sets) enables our customers to prepare for successful day-1 reporting under these harsh conditions.

And what about you? What are the costs to your business for potentially delivering incorrect, incomplete or missing data? To learn more about how you can provide the right data on time, every time, please visit www.datavalidation.me

Question: What do American Airlines, Liberty Mutual, Discount Tire and MD Anderson all have in common?

Is it?

Agile Data Integration

a) They are all top in their field.

b) They all view data as critical to their business success.

c) They are all using Agile Data Integration to drive business agility.

d) They have spoken about their Data Integration strategy at Informatica World in Vegas.

Did you reply all of the above? If so then give yourself a Ding Ding Ding. Or shall we say Ka-Ching in honor of our host city?

Indeed Data experts from these companies and many more flocked to Las Vegas for Informatica World. They shared their enthusiasm for the important role of data in their business. These industry leaders discussed best practices that facilitate an Agile Data Integration process.

American Airlines recently completed a merger with US Airways, making them the largest airline in the world. In order to service critical reporting requirements for the merged airlines, the enterprise data team undertook a huge Data Integration task. This effort involved large-scale data migration and included many legacy data sources. The project required transferring over 4TB of current history data for Day 1 reporting. There is still a major task of integrating multiple combined subject areas in order to give a full picture of combined reporting.

American Airlines architects recommend the use of Data Integration design patterns in order to improve agility. The architects shared success-factors for merger Data Integration. They discussed the importance of ownership by leadership from IT and business. They emphasized the benefit of open and honest communications between teams. They architects also highlighted the need to identify integration teams and priorities. Finally the architects discussed the significance of understanding cultural differences and celebrating success. The team summarized with merger Data Integration lessons learned : Metadata is key, IT and business collaboration is critical, and profiling and access to the data is helpful.

Liberty Mutual, the third largest property and casualty insurer in the US, has grown through acquisitions. The Data Integration team needs to support this business process. They have been busy integrating five claim systems into one. They are faced with a large-scale Data Integration challenge. To add to the complexity, their business requires that each phase is completed in one weekend, no data is lost in the process and that all finances balance out at the end of each merge. Integrating all claims in a single location was critical for smooth processing of insurance claims. A single system also leads to reduced costs and complexity for support and maintenance.

Liberty Mutual experts recommend a methodology of work preparation, profiling, delivery and validation. Rinse and repeat. Additionally, the company chose to utilize a visual Data Integration tool. This tool was quick and easy for the team to learn and greatly enhanced development agility.

Discount Tire, the largest independent tire dealer in the USA, shared tips and tricks from migrating legacy data into a new SAP system. This complex project included data conversion from 50 legacy systems. The company needs to combine and aggregate data from many systems, including customer, sales, financial and supply chain. This integrated system helps Discount Tire make key business decisions and remain competitive in a highly competitive space.

Discount Tire has automated their data validation process in development and in production. This reduces testing time, minimizes data defects and increases agility of development and operations. They have also implemented proactive monitoring in order to accomplish early detection and correction of data problems in production.

MD AndersonCancer Center is the No. 1 hospital for cancer care in the US according to U.S. News and World Report. They are pursuing the lofty goal of erasing cancer from existence. Data Integration is playing an important role in this fight against cancer. In order to accomplish their goal, MD Anderson researchers rely on integration of vast amounts of genomic, clinical and pharmaceutical data to facilitate leading-edge cancer research.

MD Anderson experts pursue Agile Data Integration through close collaboration between IT and business stakeholders. This enables them to meet the data requirements of the business faster and better. They shared that data insights, through metadata management, offer a significant value to the organization. Finally the experts at MD Anderson believe in ‘Map Once, Deploy Anywhere’ in order to accomplish Agile Data Integration.

So let’s recap, Data Integration is helping:

– An airlines continue to serve its customers and run its business smoothly post-merger.

– A tire retail company to procure and provide tires to its customers and maintain leadership

– An insurance company to process claims accurately and in a timely manner, while minimizing costs, and

– A cancer research center to cure cancer.

Not too shabby, right? Data Integration is clearly essential to business success!

So OK, I know, I know… what happens in Vegas, stays in Vegas. Still, this was one love-fest I was compelled to share! Wish you were there. Hopefully you will next year!

A Data Integration Developer, a Data Analyst and a Business Analyst go into a bar… Heard that one? You probably didn’t. They never made it to the bar. They are still back at the office, going back and forth for the umpteenth time on the data requirements for the latest report…

Sounds familiar? If so, you are not alone. Many IT departments are struggling to meet the data needs of their business counterparts. Spreadsheets, emails and cocktail napkins have not proven themselves an effective tool for relaying data requirement by the business. The process takes too long and leaves both sides frustrated and dissatisfied with the outcome. IT does not have the bandwidth to meet the ever-increasing and rapidly changing data needs of the business.

The old-fashioned “waterfall” approach to data integration simply won’t cut it anymore in the fast-paced data-driven world. There has to be a better way. Here at Informatica, we believe that an end-to-end Agile Data Integration process can greatly increase business agility.

We start with a highly collaborative process, whereby IT and the Analyst work closely together through an iterative process to define data integration requirements. IT empowers the analyst with self-service tools that enable rapid prototyping and data profiling. Once the analyst is happy with the data they access and combine, they can use their tool to seamlessly share the output with IT for final deployment. This approach greatly reduces the time-to-data, and not just any data, the right data!

The ability to rapidly generate reports and deliver new critical data for decision-making is foundational to business agility. Another important aspect of business agility is the ability to scale your system as your needs grow to support more data, data types, users and projects. We accomplish that through advanced scaling capabilities, such as grid support and high availability, leading to zero downtime, as well as improved data insights through metadata management, lineage, impact analysis and business glossary.

Finally, we need to continue to ensure agility when our system is in production. Data validation should be performed to eliminate data defects. Trying to manually validate data is like looking for a needle in a haystack, very slowly… Automating your data validation process is fast and reliable, ensuring that the business gets accurate data all the time.

It is just as important to become more proactive and less reactive when it comes to your data in production. Early detection of data process and workflow problems through proactive monitoring is key to prevention.

Would you like to see a 5X increase in the speed of delivering data integration projects?

Would you like to provide the system reliability you need as your business grows, and ensure that your business continues to get the critical data it requires without defects and without interruption?

To learn more about how Agile Data Integration can enable business agility, please check out the demonstration of the newly-released PowerCenter 9.6, featuring David Lyle, VP Product Strategy at Informatica and the Informatica Product Desk experts. This demo webinar is available on demand.

Each and every day, we strive to create the very best product possible – not just for our clients and those who judge our work but, more importantly, for ourselves. We are all perfectionists in our own right; after all, each project we undertake is a testament to our own ability.

One source of creative inspiration that I find myself drawn to time and time again is Top Chef on Bravo. For those that have not watched; the series features aspiring chefs who compete for their shot at culinary stardom and the chance to earn the title of “Top Chef.” Each episode holds two challenges for the chefs. The first is a Quickfire test of their basic abilities and the second is a more involved elimination challenge designed to test the versatility and inventiveness of the chefs as they take on unique culinary trials such as working with unusual and exotic foods or catering for a range of demanding clients. The challenges not only test their skills in the kitchen, but also uncover if they have the customer service, management and teamwork abilities required to be the Top Chef. The competing chefs live and breathe the high-pressure lifestyle that comes with being a master chef and each week someone is asked to “pack up their knives” and go home. (more…)

I am hearing an increasing number of customers tell me that they either do not have time to do data validation or reconciliation testing on their nightly updates to production systems, or that they can only test a part of the data. In the latter case, they have to “guess” which parts of the data have the most business risk and therefore deserve their testing time and resources. It doesn’t have to be this way. Informatica Data Validation can be used in production environments. The really good news is that data validation testing can be run at night from a command line script or in a workflow. The load of data into production systems can be made to be conditional on successfully passing all the tests. Customers can also build in automatic notification of the test results so that they know the status of their production systems.

The BBC published a news story where a teacher in India looked at his bank account expecting to see a balance of $200 only to find that the balance shown was $9.8 billion (480 billion rupees). Imagine that surprise!

These types of stories appear in the news on a regular basis, and the question they raise is this: How could an error of this magnitude have happened and what could have been done to prevent it? (more…)

Recently, one Sunday afternoon, my wife told me her purchased airline reservation for Monday had disappeared. A few days ago it was there, then suddenly it was gone. Apparently she was not alone. Complaints were coming in online. Support was overwhelmed. In fact, Twitter seemed to be the only way to get a quick response, so people were sending their messages and details that way!

Now, this is a great brand that I’m talking about, what I would call the chic brand in the airline industry. They had just experienced a brand-killing event. No one wants to fly an airline where reservations disappear. But the next part stunned me. When my wife finally talked to a manager at the airline, it turned out they expected this would happen! They had just migrated to a new reservation system and another airline that had done this same migration had experienced issues for a few weeks. So the airline not only expected to have similar issues, they scheduled fewer planes to fly in the upcoming weeks! (more…)

Applications are retired (sunset or decommissioned) when they become dormant or read-only. This occurs as a result of mergers and acquisitions or through modernization efforts and is a natural part of Application Information Lifecycle Management. While the applications may be no longer needed, the data they contain cannot be discarded. As a result, many organizations have hundreds, even thousands, of defunct applications that are consuming budget dollars, taking up data center space, complicating IT management, and generally just getting in the way. The challenge is getting rid of applications without getting rid of the data which is tightly coupled to them. (more…)